PREDICTIVE QUALITY SYSTEM
CONTACT DETAILS
Company: TYRIS AI, S.L.
Contact: Manuel Suárez
Phone: +34 659 001 345
Email: manuel.suarez@tyris.ai
Web: www.tyris.ai
LinkedIn: www.linkedin.com/company/tyris-ai
PROJECT DESCRIPTION
The project developed by Tyris AI involves the implementation of a predictive quality system aimed at improving the control and stability of production processes through artificial intelligence and real-time data analysis.
The solution is initially targeted at the automotive sector, although its flexible and modular approach has allowed it to be successfully adapted to other industrial sectors, such as metalworking, construction, and the water sector.
This system makes it possible to anticipate the appearance of defects in manufactured parts, optimizing production parameters and reducing the number of rejects and associated costs. Furthermore, its scalable architecture facilitates its progressive implementation on different production lines, adapting to the specific needs of each industrial plant.
Thanks to this approach, Tyris AI contributes to the digital transformation of companies, driving the automation of quality control and promoting the continuous improvement of industrial processes.
SOLUTION AND TECHNOLOGIES
Tyris AI’s predictive quality system combines advanced machine learning, neural network, and Big Data analytics to anticipate defects in production processes, thereby optimizing final quality and reducing costs associated with rejects and unplanned downtime.
The platform is based on automated, real-time data capture, integrating directly with PLCs and industrial systems to gather information from production lines without interfering with their operation. This data is stored and processed using Big Data, allowing for the historical analysis of large volumes of information and the detection of patterns that might otherwise go unnoticed at first glance.
Thanks to the use of machine learning algorithms and neural networks, the system is able to predict potential defects before they happen, analyzing the relationship between process variables and generating early alerts in the event of deviations that could compromise quality.
Tyris AI offers intelligent dashboards that visualize quality trends, patterns, and alerts in real time to facilitate analysis and decision-making, adapting to the specific needs of each production line and each user.
Furthermore, the solution is developed on a modular and scalable architecture, allowing for progressive implementation across different lines and areas of the factory, facilitating expansion as the company advances its digitalization.
Contributed innovation
Tyris AI’s predictive quality system represents a paradigm shift in industrial quality control, moving from a reactive to a predictive approach, thanks to the integration of artificial intelligence and massive data analysis into production processes.
One of its main innovations is the prediction of defects before they happen, which drastically reduces rejects, avoids rework, and lowers costs resulting from non-conforming products.
Furthermore, the system detects hidden relationships between process variables, which typically go unnoticed in traditional controls, helping to optimize production parameters and improve process stability.
Another distinguishing feature is its self-learning capacity, as neural networks progressively improve their accuracy as they process more data, adapting to the specific characteristics of each plant and production process.
The system also helps reduce downtime and downtime by anticipating quality deviations that could lead to critical failures, thereby increasing the overall efficiency of production lines.
Finally, its modular scalability allows the solution to be deployed gradually, starting with specific areas and gradually incorporating new lines and processes, without disrupting daily plant operations.
Thanks to this combination of prediction, self-learning, and modularity, Tyris AI is establishing itself as a key tool for digital transformation and the continuous improvement of production processes, especially in highly demanding sectors such as the automotive industry, where precision and quality are critical factors.
